EP 273: Microsoft PM Speaks - How AI is Shaping Product Management

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There's AI in just about all of the products that we use now, right? It seems like it everywhere you turn, whether it's, you know, your, your CRM or your marketing platform, it's. There's AI everywhere, right? But how is AI actually shaping those products right in, in the future of product management? So we're going to be talking about that today and more on Everyday AI. What's going on, y'? All? My name is Jordan Wilson. I'm the host and Everyday AI, it's your guide. It's your guide for learning and leveraging general artificial intelligence to, to or sorry, generative AI to grow your company and to grow your career. That's right, guys, we're live. Sometimes we mess up, but that's okay. So if you're listening on the podcast, thanks as always. Make sure to check out your show notes for more and make sure, as always, to go to your everydayai.com each and every day we recap our conversation for the day when we normally talk to an expert, like we do today. So make sure you check out that recap because there's going to be not just more insights from today's conversation, but also what's important going on in the world of AI news, which let's talk about that right now. The most important AI news. So first, Google has announced a slew of new updates at its IO developer conference conference. So they unveiled Project Astra, an impressive new AI agent powered by Gemini. Google announced also enhancements to its Gemini models, including Gemini 1.5 Pro and Flash. The Ask Photos powered by Gemini also was re was revealed for Google Photos. Google also demonstrated Google AI Teammate, a virtual teammate for work tasks. There's actually so many bullet points here, but two things I wanted to bring up here was one, new features for Google Search were introduced leveraging generative AI for organized search results called AI Overviews, which news publishers aren't very thrilled about. And then also Project Astra was probably the showstopper as it seemed to compete directly with kind of that live agent mode that we saw that OpenAI demoed the day before at its spring event. And while OpenAI has said that they'll start rolling out their kind of live agent mode in the coming weeks, Google has not yet given a release date yet for Project Astra. All right, speaking of OpenAI, an OpenAI co founder has left the company after months of speculation, so Ilya Sutskeverer, the co founder of OpenAI, announced that he is leaving the company. So Sutskever is the co founder and Chief Scientist of OpenAI, and he announced his departure from the company on Twitter amidst leadership turmoil and internal conflict. That leadership turmoil stems back to November, when CEO Sam Altman was fired, then rehired, and obviously the board shakeup that followed. So this also follows a series of other recognitions, resignations within OpenAI and raises questions about the company's future direction and commitment to AI safety and ethics. Also, Jan Leakey, who was the co leading the OpenAI super alignment team, also just said a couple hours ago that he resigned in a Twitter post. So a lot of shakeups there at OpenAI. All right, last but not least in the AI news, U.S. senators have proposed a budget for AI, but no regulation. So a bipartisan group of U.S. senators released a legislative plan for artificial intelligence calling for increased funding for research and development while offering few details on regulating its risks. So the plan calls for $32 billion in funding annually by 2026 for government and private sector research and development of AI. The senators also recommended creating a federal data privacy law in supporting legislation to prevent the use of deepfakes in election campaigns. The decision to delay AI regulation widens the gap between the US and other countries or regions such as the eu, which has adopted a law that prohibits risky uses of AI. So no real surprise there if you listen at the to the Everyday AI show at all. I've said for like a year that we're not going to see any meaningful, you know, AI legislation, at least here in the U.S. but it does look like senators are preparing to propose federal funding for that. So there's always more happening in the world of AI. So make sure you go to your everydayai.com and check out that daily newsletter. All right. But you probably didn't tune in to listen to me mumble and stumble through the AI news. Maybe you did. But we're to talk about the future of product management and how AI is actually shaping that. So I'm excited today to bring on our guest. There we go. We have her. Kimberly Williams is a senior Product Manager at Microsoft. Kimberly, thank you so much for joining the Everyday AI Show.

Thanks Jordan. It's really great to be here. I'm excited for the discussion today.

All right. And hey, I always have to give a special shout out to people on the West west coast who join us at, you know, 5 5am their time. So Kimberly, really appreciate you making Time for this. But can you tell us a little bit about what your role is there at Microsoft?

Absolutely. I'm a senior product manager at Microsoft. I've worked on several different products within our, what we call our Power platform suite. Mostly focused on developing no code, low code app development platforms, automation. Most recently integrating Copilot generative AI into our Business Insights Power BI product, and now working on a data unification platform, which is our fabric platform. One of the things that gets me really excited about these technologies is democratizing these technologies, making them available to customers who are not only pro users, so pro devs who maybe don't need the low code, no code, but it helps them do their job faster. But then people like me who, you know, I'm not a developer, but I want to be able to develop my own apps or automations and of course now bringing in generative AI and making that available to, to everyone. So I'm really proud of the democratization that we're doing with these technologies and then of course just improving productivity from a business perspective, but also enabling some of that creativity for our users as well.

Yeah, love, love to see it. And you know, this is just a, a reminder to our live audience here. Thanks for everyone for joining in. So, you know, Cecilia joining us from Chicago, Rolando from South Florida, Tara from Nashville, Juan from Chicago. Thank you all for joining. But now's a great time, you know, to have a senior, you know, product manager at Microsoft to get your questions in. So, you know, I'm going to start at the end here though. Kimberly. Right. So even the topic of today's episode is about the future of kind of AI and product management. So, you know, you are obviously someone that's working at a company that's creating, you know, AI that, you know, probably hundreds of millions or maybe even billions of people are already using in copilot. So, you know, I'm curious, how are you already seeing the future of kind of this intersection of AI and product management? And how do you think when we do look at the future, how is AI ultimately going to shift or change product management?

Yeah, thank you for, for the question. I think there's, there's a lot of opportunity now for using AI within the product manager role. And I'll, and I'll kind of start by thinking about, you know, breaking down what, what is the product manager role? A lot of our role is communication. And, and I'll actually take this a little higher. We'll, we'll talk about the PM role. Right. Because if you're in the space PM can mean a lot of things. You can be a product manager, program manager, project manager, and there are nuances between, but there are a couple of, of foundational things that go across all of them, which are communication, influence. And yes, we do set up a lot of meetings or we have a lot of meetings. So I will give a little nod to that. Yes, I know, but one of the things that AI can really help with in, in those spaces with communication, you know, we send, you know, when we send emails, we're often having to communicate priorities. We're often having to organize large groups of people to move toward a common, toward a common goal. And there's a way that we have, there's a way we need to communicate to drive that influence, to, to manage without, you know, to manage through influence. And you know, sometimes it can be, it can take a lot of time to craft those communications, to craft those emails. And this is an area where AI can really help you. And specifically gen AI like Copilot or if you're using Gemini or other chatgpt type gen AIs that can help you write those emails instantly. And even if it's not perfect in the way you want to send it, it hits that baseline, that template for you. Then now you only have to spend a little time tweaking rather than having to come up with the original context that sometimes we can agonize over for way longer than is really necessary.

Yeah. And, and even on that, you know, it sounds like such a low hanging fruit. Right. But you know, so, so many people time, spend hours a day both reading and, and analyzing and rereading and reanalyzing and recrafting their email. So I'm wondering, Kimberly, even from, from your personal experience, right? Like obviously, you know, Microsoft has hundreds of thousands of employees. I'm sure there's a lot of internal communications. So I, you know, I'm curious, how has AI even helped you personally in your own, you know, communication and influence as well? Right. Because you kind of connected those two things.

Yeah. And I'll actually pivot to one of the third points which is around meetings. So one of the things that has been really, really helpful about, about AI is at least for, for the meetings that we have internally in Microsoft, using Teams as our, as our meetings product. If we record, we often try to record our meetings because when we record the meetings, we get transcripts, we get notes, the AI will acknowledge, it'll recognize and acknowledge who is speaking throughout the meeting. It will recognize action items that are discussed in the meeting. And it will. So in your after meeting notes, it'll actually outline a summary of what was discussed, tell you the action items, who the action items are assigned to. And so for me, that in the event that, well, there's two ways to leverage that. One is when you can't attend a meeting, you get very valuable insights into exactly what happened. And the most important part is what were the action items? Right. I mean, if you don't have an action item that comes out of the meeting, was the meeting really necessary? Right. Is that a meeting? That should have been an email. So having the AI that can save the time that maybe you don't even need to attend the meeting. And then for folks or times when you do attend the meeting, it drafts your notes for you so you don't have to during the meeting take your notes. The AI is listening for you. And so you basically can copy paste those, throw them in an email, send it out to your audience. So I think the meeting AI is probably the most useful and it's available to everyone, hardly have to, you know, as long as somebody hits the record button, everyone has access to the content, which is really great. So it takes the burden off of each individual person, whereas other uses of copilot, you know, it's on each person to go and use it.

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Yeah, I think some of the ways that I've used it directly are certainly to help expedite writing emails, emails that again, where I have to influence a large group of people, moving them toward a common goal. This is again one of those scenarios where you could spend an hour, maybe even more agonizing over the language, making sure you've said the right thing in the right order, being concise, because that's an area I'm not always so good at. I like to talk. I like to talk in real life. I like to type a lot in real life. So AI helps me also be concise. And it can be simple too. Like a lot of, a lot of my interactions with copilot is very much a chat GPT type interaction. So they're short, short prompts. And a lot of times what I'll do is I'll even type out something basic, whether it's to be an instruction or an example. But I'll say make this better. That probably is my most used prompt is make this better. Now in those, you know, in those cases, I did start off with some kind of template or maybe I've used a template that I've gotten from, from copilot previously and I'm just adapting it for the certain situation. But definitely drafting those emails, it takes a lot of that, I'll say emotional burden. And I. It probably sounds overly dramatic, but that is the burden that it has is mental, you know, cognitive emotional burden. When you're, when you're trying to organize these, these males because again, they're Also going to a large audience. They're going to your executive leadership. You want it to be right, you want it to be good. It's your is crazy as it sounds sometimes it's your reputation in that email. And again, I'm probably sounding very overdramatic, but those are the things that kind of come with that the AI helps reduce the burden of.

You know what, Kimberly, I don't think you're being dramatic because I also think that there's two very different types of people when it comes to email. There's people like me that don't really think about it, right. And I probably have thousands of unread emails. And then there's those people that think a lot about their emails and they, you know, always read and respond instantly. And they put a lot of, you know, thought and effort into making sure that that unspoken communication speaks pretty loudly. And I love what you said there. Just something as simple as three words like make this better. You know, you don't have to over complicate, you know, when you're prompting inside Copilot or these other systems. So, you know, I'm wondering what's the one biggest, right, because you, you have access to, you know, Copilot and I'm sure you've been using it for much longer than the general public. But what is the one biggest or best use case for you personally that's helped you in your role in product management? That you look back at it and say, wow, without me using AI in this way, I don't know if I would have been able to accomplish what I have.

Yeah, I think one of the things we haven't talked about yet, and it is really important in product management is customers. That's another area that is very unique to the product manager role is we talk to customers and often we are talking with customers to understand how they feel about a product. We could either be solving a solution for them or we could be getting feedback from them on new features or how to solve a challenge that they have that in a way that they want to use a product or think about. Now that AI is here, you know, customers are, they have questions, right? They want to, they, they. We want to. We have an opportunity to dispense dispel myths about AI. We have the opportunity to understand from customers what they're excited about in AI that helps us know what we can build that will help our customers. And so to that point, when we get feedback from customers, it is, it's variable. You could have 10 customers all telling you generally the same thing. But the way they say it, that open text format makes it harder to kind of pull those common themes together. And this is a space that AI has been really helpful, especially when we're not just talking about 10 customers, we're talking about hundreds of customers, thousands of customers, maybe millions of customers. And having all of that feedback in these variable text formats. You can, you can use copa, we have used Copilot to say, you know, what are the leading themes here? You know, and this takes the burden off of reading 100 unique translations of what the customer thinks and feels about a product or an experience. So AI can help find those patterns. And what's great is not only that it can do that faster for you, but sometimes AI can even find things that you wouldn't find yourself. Because when we do put ourselves in that cognitive load, sometimes we also, we see what we want to see. That is one thing that I'll say, AI, I'll say something that I'm sure people are going to argue with me a little bit. There are some ways that AI can be unbiased, you know, but that's a little different than the other kind of bias that we often talk about. But when we're talking about interpreting what's being said by customers, when we read the context of customers, a lot of times we might read what we want to read, right? We want to read that they love our products, we want to read that they want the feature that we want to build. But AI will look at it from a different lens, right? The AI doesn't really care what you build. It's gener, you know, it's looking unbiased at that, at that feedback. So that's been, I think the greatest opportunity in product management is, is helping us get to those insights not only faster, but then seeing it in a way we wouldn't have seen without that assistance.

That's, that's such a great point, Kimberly, because, yeah, I'm, I'm not a product manager, but I can assume that there's always a pretty heavy bias, right, when you're looking at customer feedback and like, ah, you know, maybe they're, they're upset about this but, you know, maybe they just don't understand. Right. So, you know, that's, that's a, that's a really good point.

They just don't understand.

Yeah, yeah, yeah, kind of, yeah, know, taking away those, those rose colored glasses and you know, helping you maybe better understand, you know, humans, which is interesting, you know, that AI can help in that way, you know, what about when it, you know, when you think of, you know, product strategy and, you know, product roadmaps, because I'm sure that's a big part of what you do in product management. You know, so it makes sense how, you know, AI and large language models can help make sense of, you know, human feedback and unstructured data. Right. When we talk about that aspect of it. But what about when it comes to strategizing or the future of products? Right. Whether we're talking Microsoft or elsewhere, how do you think that AI can help in that regard?

Yeah, I think the. Again, this kind of comes back to. Well, I'll start by. When we build out a roadmap, often we're looking at there's multiple things that kind of come into that plan. One is we're trying to understand what direction we want to take our existing products. And that direction can either come through our customer feedback, it can also come from what we understand about the emerging landscape. Right. Like a year ago, nobody was asking for AI or generative AI. We jumped on that. We saw the opportunity, of course, we have that partnership with OpenAI. And now, more than a year in development, our customer, like every customer, is chomping at the bit to have access to copilot. So we're taking our feedback from our customers, what we understand about the emerging landscape and the opportunity, and then pulling those two together. And I think where AI can really help us with that strategy is again, as we collect customer feedback, understanding the themes that are coming through. Because again, we don't want to build, of course, we do want to build what's cool and what's exciting, but we also want to build what customers need and what they want. I mean, they're not, you know, you know, that's, that's what we're in the business to do, is to help our customers. And so I think, you know, that's where AI can help us. And, you know, before we had AI, there was a lot more, I think, manual effort in understanding what is happening on the emerging landscape. And this now is an area not to say we wouldn't still do some of that manual load. Like, I love reading about emerging trends and emerging technologies and I'm involved in a lot of forums, but I do think there's an opportunity where AI can help with that too. Where AI not only can help you review. Like, when I think of all the places I get data and information from, I have to go and I have to read every newsletter, I have to go to every forum and you know, on A certain cadence. I can provide that summary. Right? I can go to all those places almost instantaneously and provide a summary. So it can help me understand that landscape and maybe even More so, because AI now can also reach beyond, you know, the 10 forums I follow. It can reach out to a thousand forums. And so those are the things that can help us build our strategy or understand the opportunities and then talk to customers about it. I mean, there are times where we have very close customers that we work with under NDA, where we might throw an idea on the table, be like, hey, what do you think about this? You know, if we worked on something like that, would that be helpful for you? Would. Would that be something you'd be interested in? And then that can help us guide, you know, what might be the next really cool thing. Yeah.

And, you know, speaking of that, you know, Kimberly, the next cool thing. And you talked about emerging trends and technologies and in AI, you know, obviously working at Microsoft, right? Like, I think you all are in a very unique position. You know, just kind of, you know, the Microsoft MAI one. And then, you know, I know that Microsoft is already, you know, implementing the new GPT4O, right? So you have all of this very powerful technology, you know, not just from Microsoft, but other companies as well. You know, it's been a very busy week in AI. So I, I think people always naturally start to see the progression of, of these models and new capabilities, and they start to think, how is this going to impact my industry, you know, in the long run? Right? There's obviously all of these positive insights that, that you just, you know, talked about. But then there's the, okay, what if the AI gets too good? What if the next model from, from OpenAI or Microsoft is way better than me at everything? So, you know, when you talk about that and even like, okay, could AI replace the role of a product manager, what are your thoughts on that?

Well, Jordan, I have a bit of a controversial view on that, so we'll throw this out there. So it's my opinion that PMs will not, product managers will not be replaced by AI in the near future.

The.

Controversial piece of that is I would say software developers have a greater chance of being replaced before PMs. And I'll just let that sit there for half a second. I wait for people to come yell at me. Here's why. When we think about what AI is most capable of doing, it's most capable of following a formula. It's most capable of, you know, it's being trained, and it's forming these, these definitions. And when we think about what, you know, we talked about, product management, being about communication, being about influence, those are very nuanced. It's not just a formula. There's nuance between how you communicate in different audiences, how you influence in different audiences, how you talk to customers. When we think of software development, not only do folks get degrees in computer science, they have degrees in mathematics. It's very formula driven, it's very defined. I'm not saying there can't be some creativity involved in there also, but it's defined. And in fact, when we think about some of the earliest copilots that were available, one of the first co pilots was GitHub copilot. GitHub is our software development open source platform. So I think, you know, for the PMs that are worried about AI replacing our jobs. Not so fast.

Love it, love it. Saving, saving the hot takes for the end of the episode. I love it, Kimberly. And you know, I don't, I don't think that you're alone in that thought. You know, even, you know, Nvidia's CEO Jensen Wong said something similar. Right. And emphasize the, actually the importance of what you're saying. You know, communication, soft skills, being able to, you know, talk nicely to a model to prompt it to get better results. Right. And have a conversation with AIs, which I think is incredibly important. A couple, couple questions. I'm not sure if we'll have time to get to all of them, but I, I like this one here from Cecilia. So Cecilia, thanks for the question. So she's asking what is the best result you have seen from the democratization AI has brought and what has AI missed in democratizing what you do? Cecilia, with the tough questions right after your hot take. Kimberly. So what are your thoughts there?

Let me think about that. The best result you've seen from the democratization and AI has brought. What has AI missed in democratizing? I think one of the things that I think is really great about. Let's start with the first part, democratizing AI. This is one of the things that I think has been amazing. When OpenAI released ChatGPT, this is like November 2022. So we're just over a year, year and a half, but it was available to anyone and everyone who had access to their Internet website and it was free. And I think there's so many times when new technologies or new developments aren't available to everyone and they're not available in a way that people know how to use them. Chat GPT Again, I'll say something maybe a little bit controversial. When we think of ChatGPT from sort of a foundational level, it's basically like a super hyper Google, Google Search, right? I mean that's initially how a lot of people use it is they went into ChatGPT, they typed in something that you could have easily typed into Google Search and then you get a result. Now your result that you get is a little different, right? You might get a more summarized result. So like the output looks different. But the point was it gave everyone the opportunity to get on this AI wave without leaving so many people behind. So the opportunity is there, whether or not people got on board. What has democratization, what does AI miss in democratizing? What I do, I think I, I don't know if I would categorize it so much as what's been missed, but I think the, the, one of the challenges is AI is moving so fast, right? And that's the thing with democratization. You have some people like myself who are very interested, probably everyone here in this forum, right? We're all very interested in new technologies. We're very interested in AI. We are jumping on the bandwagon. There are other people who are. And it's moving so fast. So we're getting, so what started out as being an equal opportunity, we're already kind of seeing this divergence of the people who are jumping on and learning and getting way ahead. I mean, look how fast these models are developing and new versions are coming out. And those of us who are already in it, we're already like learning all the new stuff. And there's still, there's still a large group of people that are, you know, they're still somewhat suspicious of AI. You know, the Terminator movie isn't helping us very much right now. A lot of people see those worst case scenarios rather than the, the opportunistic scenarios. So yeah, I, I see that right now as kind of being the opportunity.

Yeah, and you bring up a great point. That's something I think I talked about on the show earlier this week is, you know, it seems like, I don't know, even, especially like the last week with, you know, big announcements from, from Google, from OpenAI. You know, it's, it's almost like the divide that can exist between those that do use AI and do not use AI now is even greater. Right. So with all of these new and exciting possibilities, I think also that divide between, you know, the uses and the do not use just grows exponentially, which, you know, it's kind of crazy to think about, but maybe we'll, we'll, we'll go with something much easier here. But I, I love this very practical question here from Douglas. So Douglas, thanks for your question and tuning in as always. So asking what are the top publicly available tools that you use for PM work and what productivity increase might you estimate that these tools have allowed, such as an X percent increase in whatever productivity savings etc? So what are those top tools and what kind of productivity increases can really might might people see?

Yeah, well, top tools I would say Microsoft Copilot publicly available if you are accessing it through Bing search. At one point it was called Bing Chat and now when you go to Bing you'll see it named as Copilot. I do also use Gemini from from Google. I'm now starting to experiment with meta AI and sometimes I'll go to to actual OpenAI and use chat GBT. But but those a lot of times I use admittedly I often use AI outside of our Microsoft products. You know, right now, Microsoft products, we're trying to bring Copilot into almost everything, right into Power, BI, Excel, PowerPoint, everything, you name it teams. And I have used AI in all those. But when I think about my regular daily usage, I'm often just using a chat GPT function essentially. And I would say productivity increase. I I would rather than think of it as a percent increase, I would really think about it more in terms of time saved. I mean you could still do the calculation, but I would definitely say a couple of hours. I would say one to two hours a day. Just being able to very rapidly generate communications, being able to leverage the meetings AI. So whether it's leveraging those notes, actioning on the action items that were identified in the notes, but I think it's, it's important to, and maybe I'll just, I'll kind of build on this question to, to another point that I'd like to, to share broadly with the audience, which is, you know, the hype, while the hype of AI might sizzle, AI itself will not go away. AI is going to be part of everyone's job. We'll say everyone whose job is on a computer AI is going to be part of your job at some point in time, whether your employer is going to expect you to use AI within your role within the org, or you're using it outside of your job function just to help you do it better. And I think there's, there's an opportunity there to, to start with something small like even if you're not being asked to use AI within your, within your company, within your organization. You know, do something that's fun. Like I think some of the first AI you know, other than, you know, playing with chat GBT is I played with Dolly creating pictures. Mid Journey is one of my favorites. So I've spent some time on Mid Journey just doing fun stuff that really didn't have anything to do with anything. But one of the things that also helped me understand was effective prompting because I do think like when we talk about your percentage improvement of productivity, AI is very generative AI is very easy to use, but you get your best outputs and your best productivity when you, when you really lock down your, your prompting and asking the right question. Here we go again. Using the right words. So now you're going to agonize over the right words to use in your, your AI prompting. But there's, but that's the opportunity is just start to get comfortable with AI.

That's, that's such great, you know, that's such great advice because it's something I tell people all the time. You know, because people are always trying to place, you know, generative AI on, on a hype cycle or look at this Gartner, you know, and I'm like, no, that's not how AI works. You know, I tell people like replace the word AI with Internet and it's like, do you work on the Internet? Do you use the Internet? Does the Internet help you grow? Does it help you learn? Right, so just swap out the word generative AI and I think that's, you know, pretty applicable. So you know, as we, as we wrap up here, you know, Kimberly, because we've talked about a lot from, you know, AI can help take the emotional burden off in your soft skills and help you influence to how AI can specifically help with product management and help find better insights and customer feedback and better impact the direction of future products. But you know, maybe what is your, your one biggest takeaway for people working in or around product management and how AI can really help them, you know, in their future using it?

Yeah, I think there's, there's, there's two things that I would love to, to highlight. One is as a product manager, one of our, one of the key aspects of our role is to talk to customers and I think we have a real opportunity to as we talk with customers to inform them about AI. So dispel any myths. Some customer. There's change management that's involved with AI and that's really a change management across all of Us, right. It's not just a product, product management, it's not just, you know, customers, but there's this, there's a global shift that, in how we think about and use AI, both at work as well as personally and I think as product managers, because we have that, that direct connection with our customers, we have the opportunity to hear their concerns, understand what some of that change management shift looks like and what's needed. We also get to hear from customers the art of the possible with AI. Like they also come to us with ideas and ways that they want to use AI. So I think one is being that listening conduit with our customers specifically with regard to AI. But then also when we collect feedback from customers, whether it's directly through a conversation or if we're having surveys or we have feedback forums where customers can still leave digital feedback using AI to help sift through and translate all of that variable text feedback so that we can have real insights that we can take to action for our customers. So I think that's, that's the main thing from a product manager perspective. And then I'll just say again, I think everyone, you know, AI isn't going away the more we get comfortable with using it. I think everyone can be successful in this space. Space. And if you're not already using it or you don't, you know, some companies don't have AI. They don't, they don't allow AI in the company. So there is an opportunity outside to, to play with chat GPT or play with, you know, Dolly or mid journey creating images, just anything that's fun because then that also takes away the burden of, you know, I have to, I have to be productive with this thing because your first couple things might not be as productive as you want it to be. Again, it kind of comes back to, you know, the value of the output that you get is somewhat related to the value of the input that you put in. So good prompt generally can give you good output.

This, this has been an amazing conversation. My gosh, y', all. I, I have 19 main points, right, that I somehow have to boil down in a newsletter where we normally go over the, the top three. I'm gonna have to use AI Kimberly to help me here. I'm gonna go into co pilot and see if it can help me. But so, so much great information on today's show. Kimberly, thank you so much for joining the everyday AI show. We really appreciate it.

Thank you, Jordan. Thank you everyone. It's been a really great conversation. Thank you so much for having me.

All right. And hey, as a reminder, y', all, yeah, there's a lot there. So if you haven't already, make sure to go to your everydayai.com I'm a human. I'm going to be typing up this newsletter, but I'm going to honestly need help from AI because there's so much helpful here. So make sure you check out today's newsletter and if this was helpful, please share it with a friend. If you're on LinkedIn, please go, go repost it. Leave us a review on Spotify. Follow us Spotify, Apple, all that good stuff. Thank you for tuning in. We hope to see you back tomorrow and every day for more Everyday AI. Thanks y'.

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